VP Data Architecture

Summary

The VP of Data Architecture serves as a senior leader responsible for designing, implementing, and advancing a modern, scalable, and compliant enterprise data environment for Mid Minnesota Federal Credit Union. This role blends strategic vision with hands-on technical execution to ensure data is trusted, accessible, secure, and actionable across the organization.

The position establishes the multi-year data architecture roadmap, leads analytics enablement, embeds strong governance and documentation practices, and partners closely with executive leadership, IT, Risk, and business teams to support decision-making, regulatory compliance, operational efficiency, and enhanced member experience.

Fundamental Responsibilities

• Maintain the highest standards of Integrity, Personal Responsibility, Sense of Community, and Teamwork by self-example within and outside the credit union.
• Build internal trust and confidence in organizational data through accuracy, transparency, and reliability.
• Partner with leaders and teams to translate business needs into scalable, well-governed data solutions that drive measurable outcomes.

Key Responsibilities

Data Strategy & Architecture Leadership

• Define and maintain a multi-year enterprise data architecture roadmap aligned with strategic goals.
• Establish a clear target-state architecture for data ingestion, integration, storage, modeling, analytics, and reporting.
• Prioritize initiatives based on business value, regulatory requirements, risk reduction, and operational efficiency.
• Develop and oversee member data strategies to identify growth and engagement opportunities.
• Design and lead a Data Literacy program for management and staff to ensure dashboards and analytics drive actionable, data-informed decisions and a durable data-driven culture.

 

Hands-On Technical Execution

• Architect and maintain data pipelines, integrations, and warehouse environments.
• Design scalable data models supporting analytics, AI/ML, and regulatory reporting.
• Build and manage integrations across core systems and vendors.
• Remain actively involved in coding, testing, and deployment.

Analytics, Reporting & Decision Enablement

• Advance analytics maturity from descriptive to predictive insights.
• Enable executive, operational, and regulatory reporting with trusted data.
• Support governed self-service BI capabilities.
• Ensure analytics answer real operational and strategic questions.

Governance, Compliance & Risk Management

• Establish enterprise data governance standards.
• Ensure compliance with NCUA, FFIEC, BSA, and audit expectations.
• Partner with Risk, Compliance, Audit, and IT Security teams.
• Support BSA/AML and other regulatory reporting with auditable data.
• Define governance components including data ownership and stewardship, data quality controls, metadata management, data lineage, retention policies, access controls, and monitoring and validation of reporting outputs.

 

Technical Documentation & Standards

• Maintain architecture diagrams and data dictionaries.
• Document ETL/ELT workflows, integrations, and runbooks.
• Ensure documentation supports audit readiness and onboarding.
• Maintain standardized artifacts including API and integration specifications, operational support documentation, and user guides.

 

Team Leadership & Culture Building

• Mentor and develop data engineering and analytics staff.
• Build a data-driven, documentation-driven culture.
• Establish standards, expectations, and career pathways.
• Manage data partner and vendor relationships.
• Function as a trusted cross-functional partner to executive leadership, line-of-business leaders, IT, Risk, and Operations, translating technical concepts into business terms and influencing prioritization and investment decisions

 

Qualifications

Education

• Bachelor’s degree in Computer Science, Information Systems, Data Analytics, or related field required.

Experience

• 10+ years of progressive experience in data architecture, engineering, or analytics.
• Enterprise-scale data environment design experience.
• Leadership experience in financial services or regulated industries preferred.
• Experience supporting regulatory and audit reporting.
• Proficient in SQL

 

Key Outcomes (Measures of Success)

• Accurate, reliable, and compliant enterprise data.
• Timely, actionable insights for decision-making.
• Scalable and well-documented data architecture.
• Increased organizational trust in data.
• Sustained regulatory readiness and staff development.
• Reduced single-points-of-failure through documentation, cross-training, and data literacy uplift.